NER for Hindi language using association rules
Arti Jain, Divakar Yadav, Devendra Kr. Tayal · 2014
In this paper, we propose a state-of-art association rule mining algorithm for Hindi NER. Association rules are one of the key components of the data mining. Mined rules are of - TYPE 1, TYPE 2 and Type 3 i.e. dictionary, bi-gram and feature rules respectively. We consider corpus of news articles (100 training and 50 test sets) from leading Hindi newspapers. Hindi NER shows significant increase in performance when TYPE 2 rules are combined with TYPE 1 or with TYPE 3.